At-home testing for respiratory viruses: a minireview of the current landscape.

The landscape of at-home testing using over-the-counter (OTC) tests has been evolving over the last decade. The United States Food and Drug Administration Emergency Use Authorization rule has been in effect since the early 2000s, and it was widely employed during the severe acute respiratory syndrome coronavirus 2 pandemic to authorize antigen and nucleic acid detection tests for use in central laboratories as well as OTC. During the pandemic, the first at-home tests for respiratory viruses became available for consumer use, which opened the door for additional respiratory virus OTC tests. Concerns may exist regarding the public's ability to properly collect samples, perform testing, interpret results, and report results to public health authorities. However, favorable comparison studies between OTC testing and centralized laboratory test results suggest that OTC testing may have a place in healthcare, and it is likely here to stay. This mini-review of OTC tests for viral respiratory diseases will briefly cover the regulatory and reimbursement environment, current OTC test availability, as well as the advantages and limitations of OTC tests.

Evaluating the state of the art in missing data imputation for clinical data.

Clinical data are increasingly being mined to derive new medical knowledge with a goal of enabling greater diagnostic precision, better-personalized therapeutic regimens, improved clinical outcomes and more efficient utilization of health-care resources. However, clinical data are often only available at irregular intervals that vary between patients and type of data, with entries often being unmeasured or unknown. As a result, missing data often represent one of the major impediments to optimal knowledge derivation from clinical data. The Data Analytics Challenge on Missing data Imputation (DACMI) presented a shared clinical dataset with ground truth for evaluating and advancing the state of the art in imputing missing data for clinical time series. We extracted 13 commonly measured blood laboratory tests. To evaluate the imputation performance, we randomly removed one recorded result per laboratory test per patient admission and used them as the ground truth. DACMI is the first shared-task challenge on clinical time series imputation to our best knowledge. The challenge attracted 12 international teams spanning three continents across multiple industries and academia. The evaluation outcome suggests that competitive machine learning and statistical models (e.g. LightGBM, MICE and XGBoost) coupled with carefully engineered temporal and cross-sectional features can achieve strong imputation performance. However, care needs to be taken to prevent overblown model complexity. The challenge participating systems collectively experimented with a wide range of machine learning and probabilistic algorithms to combine temporal imputation and cross-sectional imputation, and their design principles will inform future efforts to better model clinical missing data.

Rigorous evaluation of genetic and epigenetic effects on clinical laboratory measurements using Japanese monozygotic twins.

The investigation of environmental effects on clinical measurements using individual samples is challenging because their genetic and environmental factors are different. However, using monozygotic twins (MZ) makes it possible to investigate the influence of environmental factors as they have the same genetic factors within pairs because the difference in the clinical traits within the MZ mostly reflect the influence of environmental factors. We hypothesized that the within-pair differences in the traits that are strongly affected by genetic factors become larger after genetic risk score (GRS) correction. Using 278 Japanese MZ pairs, we compared the change in within-pair differences in each of the 45 normalized clinical measurements before and after GRS correction, and we also attempted to correct for the effects of genetic factors to identify Cytosine-phosphodiester-Guanine (CpG) sites in DNA sequences with epigenetic effects that are regulated by genetic factors. Five traits were classified into the high heritability group, which was strongly affected by genetic factors. CpG sites could be classified into three groups: regulated only by environmental factors, regulated by environmental factors masked by genetic factors, and regulated only by genetic factors. Our method has the potential to identify trait-related methylation sites that have not yet been discovered.

Plasma D-asparagine and the D/L-serine ratio reflect chronic kidney diseases in children regardless of physique.

Biomarkers that accurately reflect renal function are essential in management of chronic kidney diseases (CKD). However, in children, age/physique and medication often alter established renal biomarkers. We studied whether amino acid enantiomers in body fluids correlate with renal function and whether they are influenced by physique or steroid medication during development. We conducted a prospective study of children 2 to 18 years old with and without CKD. We analyzed associations of serine/asparagine enantiomers in body fluids with major biochemical parameters as well as physique. To study consequences of kidney dysfunction and steroids on serine/asparagine enantiomers, we generated juvenile mice with uninephrectomy, ischemic reperfusion injury, or dexamethasone treatment. We obtained samples from 27 children, of which 12 had CKD due to congenital (n = 7) and perinatal (n = 5) causes. Plasma D-asparagine and the D/L-serine ratio had robust, positive linear associations with serum creatinine and cystatin C, and detected CKD with high sensitivity and specificity, uninfluenced by body size or biochemical parameters. In the animal study, kidney dysfunction increased plasma D-asparagine and the D/L-serine ratio, but dexamethasone treatment did not. Thus, plasma D-asparagine and the D/L-serine ratio can be useful markers for renal function in children.

Outcome-based analytical performance specifications: current status and future challenges.

Analytical performance specifications (APS) based on outcomes refer to how 'good' the analytical performance of a test needs to be to do more good than harm to the patient. Analytical performance of a measurand affects its clinical performance. Without first setting clinical performance requirements, it is difficult to define how good analytically the test needs to be to meet medical needs. As testing is indirectly linked to health outcomes through clinical decisions on patient management, often simulation-based studies are used to assess the impact of analytical performance on the probability of clinical outcomes which is then translated to Model 1b APS according to the Milan consensus. This paper discusses the related key definitions, concepts and considerations that should assist in finding the most appropriate methods for deriving Model 1b APS. We review the advantages and limitations of published methods and discuss the criteria for transferability of Model 1b APS to different settings. We consider that the definition of the clinically acceptable misclassification rate is central to Model 1b APS. We provide some examples and guidance on a more systematic approach for first defining the clinical performance requirements for tests and we also highlight a few ideas to tackle the future challenges associated with providing outcome-based APS for laboratory testing.

Statistical considerations for some issues in clinical bridging studies evaluating companion diagnostic devices.

An in vitro diagnostic device (IVD) that is essential for the safe and effective use of a corresponding therapeutic product is commonly referred to as companion diagnostic device. Clinical trials using companion diagnostic devices (tests) together with therapies can yield the information necessary to address whether both products are safe and effective. A clinical trial ideally assesses safety and effectiveness of a therapy, where the clinical trial enrolls subjects based on the final market ready companion diagnostic test (CDx). However, such a requirement may be difficult to accomplish or impractical to achieve at the time of the clinical trial enrollment, due to unavailability of the CDx. Instead, clinical trial assay(s) (CTA), which are not the final marketable product, are often used in enrollment of patients in a clinical trial. When CTA is used for subject enrollment, a clinical bridging study provides a mechanism to bridge the clinical efficacy of the therapeutic product from CTA to CDx. This manuscript reviews some issues and challenges commonly associated with clinical bridging studies, including missing data, use of local tests for enrollment, prescreening before enrollment, and evaluation of CDx for low positive rate biomarkers, with particular focus on clinical trials using a binary endpoint and provide alternative statistical methodologies to assess effectiveness of CDx.

Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study.

BACKGROUND: Although patients have easy access to their electronic health records and laboratory test result data through patient portals, laboratory test results are often confusing and hard to understand. Many patients turn to web-based forums or question-and-answer (Q&A) sites to seek advice from their peers. The quality of answers from social Q&A sites on health-related questions varies significantly, and not all responses are accurate or reliable. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to have their questions answered. OBJECTIVE: We aimed to assess the feasibility of using LLMs to generate relevant, accurate, helpful, and unharmful responses to laboratory test-related questions asked by patients and identify potential issues that can be mitigated using augmentation approaches. METHODS: We collected laboratory test result-related Q&A data from Yahoo! Answers and selected 53 Q&A pairs for this study. Using the LangChain framework and ChatGPT web portal, we generated responses to the 53 questions from 5 LLMs: GPT-4, GPT-3.5, LLaMA 2, MedAlpaca, and ORCA_mini. We assessed the similarity of their answers using standard Q&A similarity-based evaluation metrics, including Recall-Oriented Understudy for Gisting Evaluation, Bilingual Evaluation Understudy, Metric for Evaluation of Translation With Explicit Ordering, and Bidirectional Encoder Representations from Transformers Score. We used an LLM-based evaluator to judge whether a target model had higher quality in terms of relevance, correctness, helpfulness, and safety than the baseline model. We performed a manual evaluation with medical experts for all the responses to 7 selected questions on the same 4 aspects. RESULTS: Regarding the similarity of the responses from 4 LLMs; the GPT-4 output was used as the reference answer, the responses from GPT-3.5 were the most similar, followed by those from LLaMA 2, ORCA_mini, and MedAlpaca. Human answers from Yahoo data were scored the lowest and, thus, as the least similar to GPT-4-generated answers. The results of the win rate and medical expert evaluation both showed that GPT-4's responses achieved better scores than all the other LLM responses and human responses on all 4 aspects (relevance, correctness, helpfulness, and safety). LLM responses occasionally also suffered from lack of interpretation in one's medical context, incorrect statements, and lack of references. CONCLUSIONS: By evaluating LLMs in generating responses to patients' laboratory test result-related questions, we found that, compared to other 4 LLMs and human answers from a Q&A website, GPT-4's responses were more accurate, helpful, relevant, and safer. There were cases in which GPT-4 responses were inaccurate and not individualized. We identified a number of ways to improve the quality of LLM responses, including prompt engineering, prompt augmentation, retrieval-augmented generation, and response evaluation.

Contemporary laboratory assessment of acute cardiorenal syndrome for early diagnosis: A call for action.

Acute cardiorenal syndrome (CRS), categorized as CRS type 1 and 3, is defined by the interplay of acute kidney injury or dysfunction and acute cardiac disease. For optimized diagnosis and management of CRS, strategies targeting multi-organ dysfunction must be adopted. Early diagnosis of acute CRS is important to enable timely initiation of appropriate treatment to prevent serious morbidity and mortality; however, traditional biomarkers are suboptimal. Over the past 2 decades, numerous biomarkers have been investigated for a better and more rapid diagnosis of CRS. Yet, the uptake of these contemporary biomarkers has been slow, possibly owing to the use of imperfect gold-standard reference tests. We believe that there is now scope for use of contemporary laboratory test panels to improve the diagnosis of acute CRS. In this review, we briefly discuss a proposed set of biomarkers for the diagnosis of type 1 and type 3 CRS.

Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes.

BACKGROUND: Spontaneous bacterial peritonitis (SBP) is a common complication in patients with cirrhosis. The diagnosis of SBP is still mostly based on ascites cultures and absolute ascites polymorphonuclear (PMN) cell count, which restricts the widely application in clinical settings. This study aimed to identify reliable and easy-to-use biomarkers for both diagnosis and prognosis of cirrhotic patients with SBP. METHODS: We conducted a retrospective study including 413 cirrhotic patients from March 2013 to July 2022 in the First Affiliated Hospital of Guangxi Medical University. Patients' clinical characteristics and laboratory indices were collected and analyzed. Two machine learning methods (Xgboost and LASSO algorithms) and a logistic regression analysis were adopted to screen and validate the indices associated with the risk of SBP. A predictive model was constructed and validated using the estimated area under curve (AUC). The indices related to the survival of cirrhotic patients were also analyzed. RESULTS: A total of 413 cirrhotic patients were enrolled in the study, of whom 329 were decompensated and 84 were compensated. 52 patients complicated and patients with SBP had a poorer Child-Pugh score (P < 0.05). Patients with SBP had a greater proportion of malignancies than those without SBP(P < 0.05). The majority of laboratory test indicators differed significantly between patients with and without SBP (P < 0.05). Albumin, neutrophil-to-lymphocyte ratio (NLR), and ferritin-to-neutrophil ratio (FNR) were found to be independently associated with SBP in decompensated cirrhotic patients using LASSO algorithms, and logistic regression analysis. The model established by the three indices showed a high predictive value with an AUC of 0.808. Furthermore, increased neutrophils, ALP, and C-reactive protein-to-albumin ratio (CAR) were associated with the shorter survival time of patients with decompensated cirrhosis, and the combination of these indices showed a greater predictive value for cirrhotic patients. CONCLUSIONS: The present study identified FNR as a novel index in the diagnosis of SBP in decompensated patients with cirrhosis. A model based on neutrophils, ALP and CAR showed high performance in predicting the prognosis of patients with decompensated cirrhosis.

Clinical Decision Support System in laboratory medicine.

Clinical Decision Support Systems (CDSS) have been implemented in almost all healthcare settings. Laboratory medicine (LM), is one of the most important structured health data stores, but efforts are still needed to clarify the use and scope of these tools, especially in the laboratory setting. The aim is to clarify CDSS concept in LM, in the last decade. There is no consensus on the definition of CDSS in LM. A theoretical definition of CDSS in LM should capture the aim of driving significant improvements in LM mission, prevention, diagnosis, monitoring, and disease treatment. We identified the types, workflow and data sources of CDSS. The main applications of CDSS in LM were diagnostic support and clinical management, patient safety, workflow improvements, and cost containment. Laboratory professionals, with their expertise in quality improvement and quality assurance, have a chance to be leaders in CDSS.

Mining biomarkers from routine laboratory tests in clinical records associated with air pollution health risk assessment.

Clinical laboratory in hospital can produce amounts of health data every day. The purpose of this study was to mine biomarkers from clinical laboratory big data associated with the air pollution health risk assessment using clinical records. 13, 045, 629 clinical records of all 27 routine laboratory tests in Changsha Central Hospital, including ALB, TBIL, ALT, DBIL, AST, TP, UREA, UA, CREA, GLU, CK, CKMB, LDL-C, TG, TC, HDL-C, CRP, WBC, Na, K, Ca, Cl, APTT, PT, FIB, TT, RBC and those daily air pollutants concentration monitoring data of Changsha, including PM2.5, PM10, SO2, NO2, CO, and O3 from 2014 to 2016, were retrieved. The moving average method was used to the biological reference interval was established. The tests results were converted into daily abnormal rate. After data cleaning, GAM statistical model construction and data analysis, a concentration-response relationship between air pollutants and daily abnormal rate of routine laboratory tests was observed. Our study found that PM2.5 had a stable association with TP (lag07), ALB (lag07), ALT (lag07), AST (lag07), TBIL (lag07), DBIL (lag07), UREA (lag07), CREA (lag07), UA (lag07), CK (lag 06), GLU (lag07), WBC (lag07), Cl (lag07) and Ca (lag07), (P < 0.05); O3 had a stable association with AST (lag01), CKMB (lag06), TG (lag07), TC (lag05), HDL-C (lag07), K (lag05) and RBC (lag07) (P < 0.05); CO had a stable association with UREA (lag07), Na (lag7) and PT (lag07) (P < 0.05); SO2 had a stable association with TP (lag07) and LDL-C (lag0) (P < 0.05); NO2 had a stable association with APTT (lag7) (P < 0.05). These results showed that different air pollutants affected different routine laboratory tests and presented different pedigrees. Therefore, biomarkers mined from routine laboratory tests may potentially be used to low-cost assess the health risks associated with air pollutants.

Prognostic significance of frailty status in patients with primary lung cancer.

Lung cancer has one of the highest morbidity and mortality rates in the world. Frailty is common in many countries and is a major cause of premature functional decline and premature death in older adults, and may affect the treatment and prognosis of lung cancer patients. To investigate the predictive value of frailty at diagnosis on all-cause mortality in lung cancer patients, this study retrospectively collected and analysed clinical information on lung cancer patients from 2015-2018. A total of 1667 patients with primary lung cancer were finally included in this study. The median follow-up time of patients was 650 (493, 1001.5) days. A total of 297(17.8%) patients had FI-LAB(the frailty index based on laboratory test) status of frail at the moment of diagnosis and the all-cause mortality rate for all patients was 61.1% (1018/1667). In a univariate model, we found a higher total all-cause mortality risk in frail patients (frail vs. robust, HR(hazard ratio) = 1.616, 95% CI(confidence interval) = 1.349,1.936), after balancing other variables combined into model 1 to model 6. The results were analyzed visually using ROC(Receiver operating characteristic) curves with nomogram and the AUC values ranged from 0.866-0.874. The final inclusion of age, TNM stage, CCI(Charlson comorbidity index) score, surgery history and chemotherapy into a multifactorial model balanced the predictive power of frailty grading on all-cause mortality. The study showed that for lung cancer patients, the higher the level of frailty at diagnosis, the higher the risk of all-cause mortality. In the context of widespread electronic medical records in hospitals, it is convenient and feasible to use FI-LAB to assess the prognosis of lung cancer patients.

The pre-analytical process management status and influencing factors of laboratory test before prescribing antimicrobial in developing country.

INTRODUCTION: The results of laboratory testing are crucial basis for clinicians to prescribe antimicrobial. Laboratory testing is a highly complex process, and increasing evidence suggests that errors and obstacles in the pre-analytical process (PP) will affect reasonable antimicrobial use. However, PP was an easily neglected link in hospital infection management and the current situation of it and the influencing factors of management are not clear. METHODS: A cross-sectional survey was conducted in the department of clinical, specimen collection, transportation, and inspection in 109 secondary and tertiary hospitals in Central China. The rate of antimicrobial susceptibility test request (AST) and related indexes of above departments were calculated to describe the situation. Management characteristics (frequency of training etc.) were described as proportions and fractional probit regression analysis was used to determine the influencing factors. RESULTS: The average rate of non restricted-use antimicrobial was 63%, the restricted-use was 86%, the special-use was 95%. The zero obstacle rate of specimen collection was 27.3%, of specimen transportation was 19.4% and of inspection feedback was 61.7%. There was a difference between the secondary and tertiary hospitals on non restricted-use (X2 = 22.968, P < 0.001); restricted-use (X2 = 29.466, P < 0.001); special-use (X2 = 27.317, P < 0.001). Taking non restricted-use as an example, training (OR = 0.312, 95%CI: 0.148,0.429), low-frequency appraisal (OR = 0.153, 95%CI: 0.082,0.224), guidance (OR = 0.32, 95%CI: 0.237,0.403) and information technology (OR = 0.104, 95%CI: 0.009,0.199) were positive factors. CONCLUSIONS: There were substantial differences in the rate of AST request in clinical department between secondary and tertiary hospitals. The zero obstacle rate in collection, transportation and inspection department were still low. In most departments, training and performance appraisal were positive factors, guidance and information technology were positive supporting factors.

Identification and Management of Thyroid Dysfunction Using At-Home Sample Collection and Telehealth Services: Retrospective Analysis of Real-World Data.

BACKGROUND: Programs aimed at modernizing thyroid care by pairing at-home sample collection methods with telehealth options may serve an important and emerging role in thyroid care. OBJECTIVE: The primary objective of this analysis was to evaluate telehealth use, demographics, and clinical characteristics of a cohort of consumer-initiated at-home laboratory thyroid test users who were also offered the option of follow-up telehealth consultations. METHODS: This was a retrospective analysis of real-world data from a deidentified consumer database of home-collected, mail-in thyroid tests used from March to May 2021 (N=8152). The mean age was 38.6 (range 18-85) years, and 86.6% (n=7061) of individuals identified as female. RESULTS: In total, 7% (n=587) of test takers fell into a thyroid dysfunction category (overt hypothyroidism: n=75, 0.9%; subclinical hypothyroidism: n=236, 2.9%; overt hyperthyroidism: n=5, 0.1%; and subclinical hyperthyroidism: n=271, 3.3%). Overall, 12% (n=984) of the overall sample opted into a telehealth consultation, with 91.8% (n=903) receiving a nontreatment telehealth consultation and 8.2% (n=81) receiving a treatment telemedicine consultation. Furthermore, 16% (n=96) of individuals with overt or subclinical thyroid dysfunction engaged in telehealth consultations. The majority of treatment consultations (59.3%, n=48) were conducted with people reporting a history of thyroid issues, with 55.6% (n=45) of people indicating wanting to discuss their current thyroid medication and 48% (n=39) receiving a prescription medication. CONCLUSIONS: The combination of at-home sample collection and telehealth is an innovative model for screening thyroid disorders, monitoring thyroid function, and increasing access to care, which can be implemented at a large scale and across a wide range of age groups.

Patient and Health Care Provider Perspectives on Patient Access to Test Results via Web Portals: Scoping Review.

BACKGROUND: A frequently used feature of electronic patient portals is the viewing of test results. Research on patient portals is abundant and offers evidence to help portal implementers make policy and practice decisions. In contrast, no comparable comprehensive summary of research addresses the direct release of and patient access to test results. OBJECTIVE: This scoping review aims to analyze and synthesize published research focused on patient and health care provider perspectives on the direct release of laboratory, imaging, and radiology results to patients via web portals. METHODS: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. Searches were conducted in CINAHL, MEDLINE, and other databases. Citations were screened in Covidence using the inclusion and exclusion criteria. Primary studies that focused on patient and health care provider perspectives on patient access to laboratory and imaging results via web portals were included. An updated search was conducted up to August 2023. Our review included 27 articles-20 examining patient views, 3 examining provider views, and 4 examining both patient and provider views. Data extraction and inductive data analysis were informed by sensitizing concepts from sociomaterial perspectives, and 15 themes were generated. RESULTS: Patient perspectives (24 papers) were synthesized using nine themes: (1) patterns of use and patient characteristics; (2) emotional response when viewing the results and uncertainty about their implications; (3) understanding test results; (4) preferences for mode and timing of result release; (5). information seeking and patients' actions motivated by viewing results via a portal; (6) contemplating changes in behavior and managing own health; (7) benefits of accessing test results via a portal; (8) limitations of accessing test results via a portal; and (9) suggestions for portal improvement. Health care provider perspectives (7 papers) were synthetized into six themes: (1) providers' view of benefits of patient access to results via the portal; (2) effects on health care provider workload; (3) concerns about patient anxiety; (4) timing of result release into the patient portal; (5) the method of result release into the patient portal: manual versus automatic release; and (6) the effects of hospital health information technology system on patient quality outcomes. CONCLUSIONS: The timing of the release of test results emerged as a particularly important topic. In some countries, the policy context may motivate immediate release of most tests directly into patient portals. However, our findings aim to make policy makers, health administrators, and other stakeholders aware of factors to consider when making decisions about the timing of result release. This review is sensitive to the characteristics of patient populations and portal technology and can inform result release framework policies. The findings are timely, as patient portals have become more common internationally.

Temporal Change in the Use of Laboratory and Imaging Tests in One Week Before Death, 2006-2015.

BACKGROUND: To analyze the trends in laboratory and imaging test use 1 week before death among decedents who died in Korean hospitals, tests used per decedents from 2006 to 2015 were examined by using the National Health Insurance Service-Elderly Sample Cohort (NHIS-ESC) dataset. METHODS: The study population consisted of decedents aged ≥ 60 years old with a history of admission and death at a hospital, and tests recorded in the payment claims for laboratory and imaging tests according to the Healthcare Common Procedure Coding System codes were examined. Twenty-eight laboratory and 6 imaging tests were selected. For each year, crude rates of test use per decedents in each age and sex stratum were calculated. Regression analysis was used to examine the temporal changes in the test use. RESULTS: During the follow-up period, 6,638 subjects included in the sample cohort died. The number of total laboratory and imaging tests performed on the deceased increased steadily throughout the study year from 10.3 tests/deceased in 2006 to 16.6 tests/deceased in 2015. The use of tests increased significantly in general hospitals, however, not in nursing hospitals. Laboratory tests showed yearly increase, from 9.46/deceased in 2006 to 15.57/deceased in 2015, an annual increase of 7.39%. On the other hand, the use of imaging increased from 0.86/deceased in 2006 to 1.01/deceased in 2015, which was not statistically significant. CONCLUSION: The use of tests, especially laboratory tests, increased steadily over the years even among those elderly patients at imminent death. Reducing acute healthcare at the end of life would be one target not only to support the sustainability of the health care budget but also to improve the quality of dying and death.

Dealing with missing data in laboratory test results used as a baseline covariate: results of multi-hospital cohort studies utilizing a database system contributing to MID-NET® in Japan.

BACKGROUND: To evaluate missing data methods applied to laboratory test results used for confounding adjustment, utilizing data from 10 MID-NET®-collaborative hospitals. METHODS: Using two scenarios, five methods dealing with missing laboratory test results were applied, including three missing data methods (single regression imputation (SRI), multiple imputation (MI), and inverse probability weighted (IPW) method). We compared the point estimates of adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) between the five methods. Hospital variability in missing data was considered using the hospital-specific approach and overall approach. Confounding adjustment methods were propensity score (PS) weighting, PS matching, and regression adjustment. RESULTS: In Scenario 1, the risk of diabetes due to second-generation antipsychotics was compared with that due to first-generation antipsychotics. The aHR adjusted by PS weighting using SRI, MI, and IPW by the hospital-specific-approach was 0.61 [95%CI, 0.39-0.96], 0.63 [95%CI, 0.42-0.93], and 0.76 [95%CI, 0.46-1.25], respectively. In Scenario 2, the risk of liver injuries due to rosuvastatin was compared with that due to atorvastatin. Although PS matching largely contributed to differences in aHRs between methods, PS weighting provided no substantial difference in point estimates of aHRs between SRI and MI, similar to Scenario 1. The results of SRI and MI in both scenarios showed no considerable changes, even upon changing the approaches considering hospital variations. CONCLUSIONS: SRI and MI provide similar point estimates of aHR. Two approaches considering hospital variations did not markedly affect the results. Adjustment by PS matching should be used carefully.

Comprehensive improvements in the emergency laboratory test process based on information technology.

OBJECTIVE: To explore the application effects of information technology (IT) on emergency laboratory testing procedures. METHODS: In this study, IT-based optimisation of the emergency laboratory testing process was implemented between October and December 2021. Thus, the emergency laboratory test reports from January to September 2021 were placed into the pre-optimised group, while those from January to September 2022 were categorised into the post-optimised group. Besides, the emergency laboratory test report time, emergency laboratory test report time limit coincidence rate, error rate, and employee and patient satisfaction levels in individual months and across the whole period were described. Moreover, changes in the above indicators before and after the implementation of IT-based optimisation were explored and the application effects of IT-based optimisation were also evaluated. RESULTS: The emergency laboratory test report times after the implementation of IT-based optimisation were shorter than those before IT-based optimisation (P < 0.05). The total number of laboratory test items before and after information optimization amounted to 222,139 and 259,651, respectively. Also, IT-based optimisation led to an increase in the emergency laboratory test report time limit coincidence rate from 98.77% to 99.03% (P < 0.05), while the emergency laboratory test report error rate fell from 0.77‱ to 0.15‱ (P < 0.05). Additionally, IT-based optimisation resulted in increases in both employee satisfaction, from 80.65% to 93.55% (N = 31, P > 0.05), and patient satisfaction, from 93.06% to 98.44% (P < 0.05). CONCLUSION: The automation and IT-based optimisation of the emergency laboratory testing process significantly reduces the emergency laboratory test report time and error rate. Additionally, IT-driven optimization enhances the alignment of emergency laboratory test report deadlines and enhances the overall quality and safety of emergency laboratory testing.

Extracting laboratory test information from paper-based reports.

BACKGROUND: In the healthcare domain today, despite the substantial adoption of electronic health information systems, a significant proportion of medical reports still exist in paper-based formats. As a result, there is a significant demand for the digitization of information from these paper-based reports. However, the digitization of paper-based laboratory reports into a structured data format can be challenging due to their non-standard layouts, which includes various data types such as text, numeric values, reference ranges, and units. Therefore, it is crucial to develop a highly scalable and lightweight technique that can effectively identify and extract information from laboratory test reports and convert them into a structured data format for downstream tasks. METHODS: We developed an end-to-end Natural Language Processing (NLP)-based pipeline for extracting information from paper-based laboratory test reports. Our pipeline consists of two main modules: an optical character recognition (OCR) module and an information extraction (IE) module. The OCR module is applied to locate and identify text from scanned laboratory test reports using state-of-the-art OCR algorithms. The IE module is then used to extract meaningful information from the OCR results to form digitalized tables of the test reports. The IE module consists of five sub-modules, which are time detection, headline position, line normalization, Named Entity Recognition (NER) with a Conditional Random Fields (CRF)-based method, and step detection for multi-column. Finally, we evaluated the performance of the proposed pipeline on 153 laboratory test reports collected from Peking University First Hospital (PKU1). RESULTS: In the OCR module, we evaluate the accuracy of text detection and recognition results at three different levels and achieved an averaged accuracy of 0.93. In the IE module, we extracted four laboratory test entities, including test item name, test result, test unit, and reference value range. The overall F1 score is 0.86 on the 153 laboratory test reports collected from PKU1. With a single CPU, the average inference time of each report is only 0.78 s. CONCLUSION: In this study, we developed a practical lightweight pipeline to digitalize and extract information from paper-based laboratory test reports in diverse types and with different layouts that can be adopted in real clinical environments with the lowest possible computing resources requirements. The high evaluation performance on the real-world hospital dataset validated the feasibility of the proposed pipeline.

A Facile Fluorometric Assay of Orotate Phosphoribosyltransferase Activity Using a Selective Fluorogenic Reaction for Orotic Acid.

Orotate phosphoribosyltransferase (OPRT) exists as a bifunctional enzyme, uridine 5'-monophosphate synthase, in mammalian cells and plays an important role in pyrimidine biosynthesis. Measuring OPRT activity has been considered important for understanding biological events and development of molecular-targeting drugs. In this study, we demonstrate a novel fluorescence method for measuring OPRT activity in living cells. The technique utilizes 4-trifluoromethylbenzamidoxime (4-TFMBAO) as a fluorogenic reagent, which produces selective fluorescence for orotic acid. To perform the OPRT reaction, orotic acid was added to HeLa cell lysate, and a portion of the enzyme reaction mixture was heated at 80 °C for 4 min in the presence of 4-TFMBAO under basic conditions. The resulting fluorescence was measured using a spectrofluorometer, which reflects the consumption of orotic acid by the OPRT. After optimization of the reaction conditions, the OPRT activity was successfully determined in 15 min of enzyme reaction time without further procedures such as purification of OPRT or deproteination for the analysis. The activity obtained was compatible with the value measured by the radiometric method with [3H]-5-FU as the substrate. The present method provides a reliable and facile measurement of OPRT activity and could be useful for a variety of research fields targeting pyrimidine metabolism.